Often, we get data frames that are not of same size that means some of the rows or columns are missing in any of the data frames. Therefore, to merge these types of data frames we can merge them with all of their values and convert the missing values to zero if necessary. This can be done by using merge function and replacement of missing values NA to zeros should be done by using single square brackets.ExampleConsider the below data frames −> C1 df1 df1 C1 1 A 2 B 3 C 4 D 5 E 6 F 7 G ... Read More

In our daily life, often we want to know what will be date after some number of days. This is also required in professional life, especially in those professions where we work on projects and have tight deadlines. To find the date after a number a certain number of days we can just use plus sign after reading the date with as.Date.Example> as.Date("2001-01-01")+30 [1] "2001-01-31" > as.Date("2020-06-30")+30 [1] "2020-07-30" > as.Date("2020-06-30")+50 [1] "2020-08-19" > as.Date("2020-06-30")+100 [1] "2020-10-08" > as.Date("2020-06-30")+120 [1] "2020-10-28" > as.Date("2020-06-30")+15 [1] "2020-07-15" > as.Date("2020-06-30")+45 [1] "2020-08-14" > as.Date("2020-06-30")+40 [1] "2020-08-09" > as.Date("2020-12-25")+20 [1] "2021-01-14" > as.Date("2020-12-25")+300 [1] ... Read More

We can create plots in R with having different plot window sizes. This will be helpful when we want to express X-axis or Y-axis differently. Also, the change in the size of the plot window will help us to paste the plot in places that are short or large. For example, if we want to present the plot in a business meeting then we can increase its size and if we want to publish it in a paper then its size can be decreased.ExampleConsider the below vectors x and y −> x y plot(x, y)OutputPlotting with 10-inch-wide and 5 inch ... Read More

It is possible that we get data sets where a column contains NA as well as blank, therefore, it becomes necessary to deal with these values. One of the ways to deal with these values is selecting the rows where we do not have them. This can be done by subsetting through single square brackets.ExampleConsider the below data frame −> set.seed(1) > x1 x2 x3 df df x1 x2 x3 1 4 1 5 2 39 5 3 1 3 5 4 34 4 5 5 23 1 6 43 7 14 3 8 18 ... Read More

If we have a list that contain vectors having even number of elements in total then we can create a matrix of those elements. example, if a list contain 8 vectors and the total number of elements in those 8 vectors is 100 or any other multiple of 2 then we can create a matrix of those elements. This can be done by using unlist function inside matrix function.ExampleConsider the below list x −> x x [[1]]   [1]  1  2  3  4  5  6  7  8  9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 [[2]]   [1] 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 [[3]]   [1] 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 [[4]]   [1] 76 77 78 79 80  81 82 83 84 85 86 87 88 89 90 91 92 93 94  [20] 95 96 97 98 99 100 [[5]]  [1] 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 [20] 120 121 122 123 124 125 [[6]]  [1] 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 [20] 145 146 147 148 149 150 [[7]]  [1] 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 [20] 170 171 172 173 174 175 [[8]]  [1] 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 [20] 195 196 197 198 199 200 > Matrix_x Matrix_x      [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]  [1,]   1   2   3    4    5    6    7    8    9   10  [2,]  11  12  13   14   15   16   17   18   19   20  [3,]  21  22  23   24   25   26   27   28   29   30  [4,]  31  32  33   34   35   36   37   38   39   40  [5,]  41  42  43   44   45   46   47   48   49   50  [6,]  51  52  53   54   55   56   57   58   59   60  [7,]  61  62  63   64   65   66   67   68   69   70  [8,]  71  72  73   74   75   76   77   78   79   80  [9,]  81  82  83   84   85   86   87   88   89   90 [10,]  91  92  93   94   95   96   97   98   99  100 [11,] 101 102 103  104  105  106  107  108  109  110 [12,] 111 112 113  114  115  116  117  118  119  120 [13,] 121 122 123  124  125  126  127  128  129  130 [14,] 131 132 133  134  135  136  137  138  139  140 [15,] 141 142 143  144  145  146  147  148  149  150 [16,] 151 152 153  154  155  156  157  158  159  160 [17,] 161 162 163  164  165  166  167  168  169  170 [18,] 171 172 173  174  175  176  177  178  179  180 [19,] 181 182 183  184  185  186  187  188  189  190 [20,] 191 192 193  194  195  196  197  198  199  200 > Matrix_x Matrix_x [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]  [1,]  1  21 41 61 81 101 121 141 161 181  [2,]  2  22 42 62 82 102 122 142 162 182  [3,]  3  23 43 63 83 103 123 143 163 183  [4,]  4  24 44 64 84 104 124 144 164 184  [5,]  5  25 45 65 85 105 125 145 165 185  [6,]  6  26 46 66 86 106 126 146 166 186  [7,]  7  27 47 67 87 107 127 147 167 187  [8,]  8  28 48 68 88 108 128 148 168 188  [9,]  9  29 49 69 89 109 129 149 169 189 [10,] 10  30 50 70 90 110 130 150 170 190 [11,] 11  31 51 71 91 111 131 151 171 191 [12,] 12  32 52 72 92 112 132 152 172 192 [13,] 13  33 53 73 93 113 133 153 173 193 [14,] 14  34 54 74 94 114 134 154 174 194 [15,] 15  35  55 75 95 115 135 155 175 195 [16,] 16  36 56 76 96 116 136 156 176 196 [17,] 17  37  57 77 97 117 137 157 177 197 [18,] 18  38  58 78 98 118 138 158 178 198 [19,] 19  39  59 79 99 119 139 159 179 199 [20,] 20  40  60 80 100 120 140 160 180 200

If you have a csv file on Github then it can be directly imported in R by using its URL but make sure that you click on Raw option on Github page where the data is stored. Many people do not click on Raw option therefore they read HTML instead of CSV and get confused. Here, I am sharing a public data set that contains the list of data sets. This data set has 12 variables. Now let’s import it −> Data str(Data) 'data.frame': 57 obs. of 12 variables: $ Dataset.Name : Factor w/ 57 levels " ", "2008 Election ... Read More

If there is a category for which the frequency is significantly different from others then the X-axis labels of the bar plot using ggplot2 are automatically sorted to present the values alternatively. We might want to keep the original sequence of categories that is available in the categorical variable. Therefore, we can store the categorical variable as a factor and then create the bar plot.ExampleConsider the below data frame −> Group Frequency df df Group Frequency 1 India 12 2 USA 18 3 UK 35 4 Germany 20 > ... Read More

Create a vector with dates is not an easy task but with help of seq and as.Date it becomes easy in R. With the help of these functions we can create a vector in R that contain dates between two dates. But this cannot be done in reverse order, for example, if we want to have future date as first element of the vector then it would not be possible.Example> V1 V1  [1] "2020-01-01" "2020-01-02" "2020-01-03" "2020-01-04" "2020-01-05"  [6] "2020-01-06" "2020-01-07" "2020-01-08" "2020-01-09" "2020-01-10" [11] "2020-01-11" "2020-01-12" "2020-01-13" "2020-01-14" "2020-01-15" [16] "2020-01-16" "2020-01-17" "2020-01-18" "2020-01-19" "2020-01-20" [21] "2020-01-21" "2020-01-22" "2020-01-23" ... Read More

We might want to extract row index irrespective of its type (whether numeric or string) to do some calculations if it is incorrectly set as a row index. It happens during the data collection process or incorrect processing of data. Also, since row indexes are helpful to access row we must have proper names to them instead of values that might makes confusion. For example, if a data frame has row indexes as 43, 94, etc. then it might be confusing. Therefore, we should convert row indexes to a vector or a column if required.ExampleConsider the below data frame (Here, ... Read More

A scatterplot is used to observe the relationship between two continuous variables. If the sample size is large then the points on the plot lie on each other and does not look appealing. Also, the interpretation of such type of scatterplots is not an easy task, therefore, we can increase the transparency of points on the plot to make it more appealing. We can do this by using alpha argument in geom_point of ggplot2.ExampleConsider the below data frame −> set.seed(123) > x y df library(ggplot2) > ggplot(df, aes(x, y))+geom_point()Output> ggplot(df, aes(x, y))+geom_point(alpha=0.10)Output> ggplot(df, aes(x, y))+geom_point(alpha=0.05)OutputRead More